Theories of attention and learning differ in the roles they prescribe to memory representations. Theories of attention almost universally propose that visual working memory representations determine which objects are the focuses of processing in complex visual scenes. However, models of learning propose that after a handful of trials, the control of visual cognition should shift from being driven by visual working memory to representations in long-term memory. In this project we will bring these ideas from models of learning to bear on the processing of visual information. To test these model predictions in a definitive manner, we will develop methods of measuring electrical brain activity that we can use to track what information is being actively held in visual working memory, simultaneously with independent measures of the representations in visual long-term memory. Our preliminary data indicate that these electrophysiological tools can provide trial-by-trial indices of memory representations controlling visual cognition. Our integrated modeling and neuroscientific approach will allow us to more quickly lay a theoretical foundation for understanding the top-down control of visual processing. This can then be used to understand the nature of deficits in clinical populations and to refine potential treatments.